耐乙醇汽油橡胶材料溶胀性能的研究

从原胶、炭黑、增塑剂及硫化体系的类型对胶料在乙醇汽油中的溶胀性能的影响进行了研究。结果表明,选择橡塑合金NV7050作为原胶,加入N550与N774炭黑各40份,选择增塑剂TP-95和过氧化物硫化体系的胶料在乙醇汽油E10中体积及质量变化率较小,呈现良好的力学稳定性,耐乙醇汽油溶胀性能较好。     

基于数据融合的ECT图像重建算法

针对固定电极的ECT成像独立测量值较少和因电极位置的影响而导致重建图像失真等问题,提出了基于旋转电极ECT系统模型和数据融合方法来提高重建图像质量。本模型对16电极的ECT模型进行5次旋转,得到的数据采用两种方式进行处理:一是5组数据分别采用线性反投影(LBP)和修正共轭梯度法(MCG)进行重建,再对重建数据进行主分量分析(PCA)的数据融合;二是直接用PCA数据融合再分别进行LBP和MCG图像重建。实验证明:通过增加测量电容数,结合两种数据处理方式可明显提高重构图像质量,降低成像误差。     

Enhanced Oxidative Desulfurization of Dibenzothiophene by Functional Mo‐Containing Mesoporous Silica

Functional mesoporous Mo–SiO₂ materials were synthesized by a one‐pot and facile room‐temperature procedure, and characterized by X‐ray diffraction, TEM, Raman spectroscopy, FT‐IR, diffuse reflectance spectra, and BET analysis. The experimental results demonstrated that the mesoporous materials presented a high dispersion of molybdenum species and excellent catalytic activity for the removal of dibenzothiophene (DBT) without organic solvents as extractants. The catalytic performance on different sulfur‐containing compounds was also investigated in detail. After recycling for eight times, the removal of the oxidation desulfurization system could still reach high values. GC‐MS analysis detected the oxidation product of DBT. A mechanism was proposed for the absorptive oxidation process of sulfur compounds.     

基于Q-learning的不确定环境BDI Agent最优策略规划研究

BDI模型能够很好地解决在特定环境下的Agent的推理和决策问题,但在动态和不确定环境下缺少决策和学习的能力。强化学习解决了Agent在未知环境下的决策问题,却缺少BDI模型中的规则描述和逻辑推理。针对BDI在未知和动态环境下的策略规划问题,提出基于强化学习Q-learning算法来实现BDI Agent学习和规划的方法,并针对BDI的实现模型ASL的决策机制做出了改进,最后在ASL的仿真平台Jason上建立了迷宫的仿真,仿真实验表明,在加入Q-learning学习机制后的新的ASL系统中,Agent在不确定环境下依然可以完成任务。     

基于方向梯度直方图属性空间的局部放电模式识别改进算法

该文提出一种基于方向梯度直方图(HOG)属性空间的局部放电模式识别改进算法,旨在提高特征对样本信息的概括能力,并克服分类器对高维特征的识别局限.首先,构造局部放电脉冲序列分布(PRPS)模式作为识别依据,利用局部细分叠加窗口滑移的迭代算法自动化构建PRPS图像的HOG属性空间;然后,通过线性变换协方差矩阵的方式重构HOG属性空间,使其满足相互独立性;接着,根据属性重要性重新排列空间后,依次增加输入朴素贝叶斯分类器的属性个数,基于分类精度搜索最佳属性子集;最后,按照归约属性的相对重要性进行加权,最终设计出HOG属性选择加权朴素贝叶斯分类器.大量样本测试结果证明,此算法能够达到很高的识别精度,对传统识别算法的优化效果明显,有较好的应用价值.     

Dandelion-Like Bi2S3/rGO hierarchical microspheres as high-performance anodes for potassium-ion and half/full sodium-ion batteries

Sodium-ion batteries (SIBs) and potassium-ion batteries (PIBs) have been considered as attractive alternatives for next-generation battery systems, which have promising application potential due to their earth abundance of potassium and sodium, high capacity and suitable working potential, however, the design and application of bi-functional high-performance anode still remain a great challenge up to date. Bismuth sulfide is suitable as anode owing to its unique laminar structure with relatively large interlayer distance to accommodate larger radius ions, high theoretical capacity and high volumetric capacity etc. In this study, dandelion-like Bi₂S₃/rGO hierarchical microspheres as anode material for PIBs displayed reversible capacity, and 206.91 mAh·g⁻¹ could be remained after 1,200 cycles at a current density of 100 mA·g⁻¹. When applied as anode materials for SIBs, 300 mAh·g⁻¹ could be retained after 300 cycles at 2 A·g⁻¹ and its initial Coulombic efficiency is as high as 97.43%. Even at high current density of 10 A·g⁻¹, 120.3 mAh·g⁻¹ could be preserved after 3,400 cycles. The Na₃V₂(PO₄)₃@rGO//Bi₂S₃/rGO sodium ion full cells were successfully assembled which displays stable performance after 60 cycles at 100 mA·g⁻¹. The above results demonstrate that Bi₂S₃/rGO has application potential as high performance bi-functional anode for PIBs and SIBs.

     

CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19

Machine Learning - The coronavirus disease 2019 (COVID-19) global pandemic poses the threat of overwhelming healthcare systems with unprecedented demands for intensive care resources. Managing...